3D Object Detection on Indoor Environments
An indoor 3D perception pipeline combining stereo depth, 3D object detection, and 6D pose estimation.
Project Snapshot
| Signal | Details |
|---|---|
| Timeline | May 2021 to Sep 2021 |
| Organization | XPENG Robotics |
| Focus | 3D Object Detection on Indoor Environments |
| Stack | Custom implementation and project-specific tooling |
Pipeline
- Generate accurate point clouds using stereo-based depth estimation.
- Run 3D object detection on the generated indoor point clouds.
- Use 6D pose estimation and PnP to recover more accurate dimensions and poses for smaller objects.
- Fuse 3D object detection with 6D pose estimation for richer indoor object understanding.
Why Fusion Matters
Sparse point clouds are effective for larger objects, but smaller objects may not have enough points for reliable 3D detection. The 6D pose branch helps recover details that pure point-cloud detection can miss.